Company Description Arima provides brands and agencies with a faster, more accessible way to measure marketing performance across all channels. Unlike traditional marketing mix modeling tools that are slow, costly, and tailored mainly to data scientists, Arima is built for marketers and integrates consumer insights, media planning, performance measurement, and interactive maps in one platform. The platform is powered by Arima's Synthetic Society™, a privacy-by-design database that reflects real-world consumers using over 10,000 attributes from census data, market research, mobility patterns, and purchase behavior. Clients bring their own data while Arima supplies the infrastructure, enabling always-on measurement that aligns with how modern marketing teams operate. This environment offers data professionals meaningful opportunities to shape how marketing decisions are made at scale.

Role Description This is a full-time Data Scientist role based in Toronto, ON, with a hybrid work arrangement that allows for part-time work from home. The Data Scientist will design, build, and validate statistical and machine learning models that power Arima’s marketing performance measurement and Synthetic Society™ platform. Day-to-day responsibilities include collecting, cleaning, and transforming large datasets; conducting exploratory data analysis; and developing methodologies for attribution, forecasting, and optimization. The role involves collaborating closely with product, engineering, and marketing stakeholders to translate business questions into analytical frameworks and to present findings through clear visualizations and reports. The Data Scientist will also contribute to improving data pipelines, documenting models and assumptions, and continuously refining analytical tools based on user feedback and new data sources.

Qualifications Strong foundation in Data Science and Statistics, with experience applying statistical modeling or machine learning to real-world business problems. Demonstrated skills in Data Analytics and Data Analysis, including cleaning, transforming, and interpreting complex, multi-source datasets. Proficiency in Data Visualization, using tools or libraries (e.g., Python, R, BI platforms) to communicate insights to technical and non-technical stakeholders. Experience with programming languages commonly used in data science (such as Python or R) and working with relational and non-relational databases. Bachelor’s or advanced degree in a quantitative field such as Statistics, Computer Science, Mathematics, Economics, or related discipline. Ability to design robust experiments, validate models, and document methodologies in a clear, reproducible way. Comfort working in a hybrid environment, collaborating with cross-functional teams, and presenting complex concepts in accessible terms. Experience with marketing analytics, marketing mix modeling, or consumer data is an asset, as is familiarity with privacy-by-design or synthetic data approaches.